Overview

A deep learning model classifies eye diseases into four categories: normal, cataract, diabetic retinopathy, and glaucoma, using a dataset of over 4,000 retinal images. Achieving 92% accuracy, the model enhances early detection, enabling timely diagnosis and intervention to prevent vision loss.

Data augmentation and fine tuning techniques improve the model's robustness, ensuring reliable classification. This AI driven approach supports efficient and scalable eye disease screening, aiding healthcare professionals in detecting conditions before they progress to severe stages.